Computational investigation of dust settlement effect on power generation of three solar tracking photovoltaic modules using a modified angular losses coefficient. (1st July 2021)

• Record Type: Journal Article
• Authors: Zarei, Tahereh; Abdolzadeh, Morteza; Soltani, Madjid; Aghanajafi, Cyrus
• Is Part Of: Solar energy. Volume 222(2021)
• Page Start: 269
• Page End: 289
• Publication Date: 2021-07-01
• Subjects: Angular losses coefficient -- Solar tracking module -- Dust deposition -- Degrees of surface dirtiness -- Power generation -- Computational method; Solar energy -- Periodicals; Solar engines -- Periodicals; 621.47
• DOI: 10.1016/j.solener.2021.04.059
• Languages: English
• ISSNs: 0038-092X

Abstract

Highlights: The effect of dust accumulation on the performance of three solar tracking PV modules is investigated. The modified angular losses coefficient (αr ) is calculated at different tilt angles and a dust deposition density. The αr coefficient is used by a computational method to predict the power generation of solar tracking modules. The proper performance of the αr coefficient is examined using the results of previous experimental studies. The reduction in electricity generation and temperature distribution of the modules are calculated. Abstract: Providing a suitable method for predicting the effect of particle aggregation on photovoltaic (PV) performance can be one of the best ways to make better use of solar energy. In this study, a mathematical method was used and modified to provide a better prediction of angular losses coefficient ( α r ). The modified coefficient as well as a computational method were used to find the performance of dusty modules equipped with one-axis (East-West (EW), North-South (NS)), and dual-axis (DAT) solar tracking systems. The modified α r, which here is called the degree of surface dirtiness, can be used to estimate the area covered by particles per cm 2, i.e. A ∗ C ( θ ) . A better prediction of α r causes a better prediction of power loss due to dust settlement. Results showed that A ∗ C ( θ ) is the factor that shows the role of incidence angle in visualizing the type of dust cover, while α r shows the effect of slope angle on dust deposition density. Furthermore, combination of α r with the computational model revealed that the dirty DAT module has the least daily power loss which is 9% of the clean counterpart power. The power losses for the NS and EW dusty modules are 13% and 20.5% lower than the clean counterparts, respectively. It should be noted that the obtained results in this study are in a good compromise with the experimental and computational data available in the literature.